This article is devoted to rebuilt for an important fragmentary of wavelet models of Biomedical Signal Processing. These models were built using Haar’s fragmentary-unchanged wavelets as well as Doubechi wavelets. The Haar’s fragmentary-unchanged wavelets models has a high accuracy for Biomedical signals on digital work, and this provides doctors for making any useful decisions about the patients diseases. For example, the first signal of Gastroenterology experimental information was took, and there were built on the basis of this information the of fragmentary-unchanged and Doubechi wavelet models and evaluated their errors. It is known that modification of signals using fragmentary wavelets results in formation of orthonormal wavelets, due to there will be sharp increase in errors along the signal graph, thus in order to reduce errors Doubechi wavelets were used and achieved the goal.

This article is devoted to rebuilt for an important fragmentary of wavelet models of Biomedical Signal Processing. These models were built using Haar’s fragmentary-unchanged wavelets as well as Doubechi wavelets. The Haar’s fragmentary-unchanged wavelets models has a high accuracy for Biomedical signals on digital work, and this provides doctors for making any useful decisions about the patients diseases. For example, the first signal of Gastroenterology experimental information was took, and there were built on the basis of this information the of fragmentary-unchanged and Doubechi wavelet models and evaluated their errors. It is known that modification of signals using fragmentary wavelets results in formation of orthonormal wavelets, due to there will be sharp increase in errors along the signal graph, thus in order to reduce errors Doubechi wavelets were used and achieved the goal.